def load_openephys(folder, Experiment=1, Recording=1, TTLport=None):
"""Loads in openephys continuous and event data from processor. Openephys format ok, binary format not yet finished/vetted"""
try: # Load in openephys format
cont_array = oe.loadFolder(folder)
events = oe.loadEvents(os.path.join(folder, 'all_channels.events'))
oe_type = 'oe'
Rate = 'See cont_array variable'
except ZeroDivisionError: # load in binary format
_, PluginNames = SettingsXML.GetRecChs(os.path.join(folder, 'settings.xml'))
Proc = list(PluginNames.keys())[0] # assume first node is the recording processor
ProcName = PluginNames[Proc] # Get processor name
ProcFolderName = ProcName.replace(' ', '_') + '-' + Proc + '.0'
cont_array, Rate = ob.Load(folder, Experiment=Experiment, Recording=Recording)
Proc = list(Rate.keys())[0]
SR = Rate[Proc][str(Experiment - 1)] # get sample rate
cont_time = np.load(os.path.join(folder, 'experiment' + str(Experiment) + '/recording' + str(Recording)
+ '/continuous/' + ProcFolderName + '/timestamps.npy'))
if TTLport is not None:
event_folder = os.path.join(folder, 'experiment' + str(Experiment) + '/recording' + str(Recording) +
'/events/' + ProcFolderName + '/TTL_' + str(TTLport))
event_data = load_binary_events(event_folder)
else:
event_data = None
oe_type = 'binary'
return event_data, cont_array, SR
def load_openephys(folder):
"""Loads in openephys continuous and event data. Openephys format ok, binary format not yet finished/vetted"""
try: # Load in openephys format
cont_array = oe.loadFolder(folder)
events = oe.loadEvents(os.path.join(folder, 'all_channels.events'))
oe_type = 'oe'
Rate = 'See cont_array variable'
except ZeroDivisionError: # load in binary format
cont_array, Rate = ob.Load(folder)
SR = Rate['100']['0'] # get sample rate
cont_time = np.load(
os.path.join(
folder,
'experiment1/recording1/continuous/Rhythm_FPGA-100.0/timestamps.npy'
))
event_folder = os.path.join(
folder, 'experiment1/recording1/events/Rhythm_FPGA-100.0/TTL_1')
event_data = []
for file_name in [
'channel_states.npy', 'channels.npy', 'full_words.npy',
'timestamps.npy'
]:
event_data.append(np.load(os.path.join(event_folder, file_name)))
oe_type = 'binary'
return event_data, cont_array, Rate
def events2ms(exp_folder,
Processor='100',
Experiment=1,
Recording=1,
TTLport=1):
"""
extract event times and convert to ms, with reference to recording start.
:param exp_folder:
:param Processor:
:param Experiment:
:param Recording:
:param TTLport:
:return: event_times_ms and channel_states: arrays of size (nevents,) with event timestamps in ms (0 = recording start time)
and corresponding on/off channels.
"""
event_data, timing_data = ob.LoadTTLEvents(
exp_folder, TTLport=TTLport) # load event data
# extract variables
timestamps = event_data[Processor][str(Experiment -
1)][str(Recording -
1)]['timestamps']
channel_states = event_data[Processor][str(Experiment -
1)][str(Recording -
1)]['channel_states']
start_time = int(timing_data[Processor][str(Experiment -
1)][str(Recording -
1)]['start_time'])
SR = int(timing_data[Processor][str(Experiment - 1)][str(Recording -
1)]['Rate'])
# calculate event times in ms referenced to recording start
event_times_ms = (timestamps - start_time) / SR * 1000
return event_times_ms, channel_states
elif session == '2b':
base_folder_dict = {
'nt':
r'C:\Users\Nat\Documents\UM\Working\Opto\Rat613\ClosedLoopTest2\Rat613_SWRstim_probe1_2020-08-07_10-55-22',
'posix':
r'/data/Working/Opto/Rat613/ClosedLoopTest2/Rat613_SWRstim_probe1_2020-08-07_10-55-22'
}
Experiment, Recording, set_append = 3, 1, '_3'
base_folder = base_folder_dict[os.name]
traces_ds = np.load(
os.path.join(base_folder, 'continuous_eeg' + str(Experiment) + '.npy'))
SRlfp = 1250
detection_events, detection_timing = ob.LoadTTLEvents(base_folder,
Processor='104',
Experiment=Experiment,
Recording=Recording,
TTLport=2)
stim_events, stim_timing = ob.LoadTTLEvents(base_folder,
Processor='111',
Experiment=Experiment,
Recording=Recording,
TTLport=1)
sync_start_time = int(
detection_timing[Ripple_Proc][str(Experiment - 1)][str(Recording -
1)]['start_time'])
SRoe = int(detection_timing[Ripple_Proc][str(Experiment - 1)][str(Recording -
1)]['Rate'])
detect_time_sec = (detection_events[Ripple_Proc][str(Experiment - 1)][str(
Recording - 1)]['timestamps'] - sync_start_time) / SRoe
import matplotlib.pyplot as plt
import os
import pandas as pd
import Analysis.python.LFP.helpers as lfhelp
import seaborn as sns
import matplotlib.patches as patches
## Plot settings
font = {'family': 'normal', 'weight': 'normal', 'size': 22}
plt.rc('font', **font)
## Relevant folder/files
chan_map_file = '/data/GitHub/dibalab_ephys/Channel Maps/MINT/2x32MINT_chan_map_good' # nat laptop location r'C:\Users\Nat\Documents\UM\Working\Opto\Rat613\2x32MINT_chan_map_good.txt'
data_folder = '/data/Working/Opto Project/Rat 613/Rat613Day1/Rat613simtest_2020-08-01_08-47-11/' # nat laptop location r'C:\Users\Nat\Documents\UM\Working\Opto\Rat613\Rat613Day1\Rat613track_2020-08-01_09-21-55'
## Load Data!
chan_map_dict = ob.LoadChannelMapFromText(chan_map_file)
chans_use = np.hstack((np.arange(0, 8), np.arange(16, 24))) # Use only shank 1 and shank 3
# channels_use = [chan for chan in np.asarray(chan_map_dict['0']['mapping'])[chans_use]] # not used
Data, Rate = ob.Load(data_folder, ChannelMap=chans_use, Experiment=1, Recording=1, mode='r')
event_data = ppd.load_binary_events()
channels_use = [chan for chan in np.asarray(chan_map_dict['0']['mapping'])[chans_use]]
Data, Rate = ob.Load(data_folder, ChannelMap=channels_use, Experiment=2, Recording=1, mode='r')
## Look at silencing for Jackie place stim day 2
adc_channel = 35 # channel with adc input
on_thresh = 1300000 # on voltage threshold
if os.environ['APPDATA'][0] == 'C':
base_dir = r'C:\Users\Nat\Documents\UM\Working\Opto\Jackie671\placestim_day2\PRE'
full_raw_path = r'C:\Users\Nat\Documents\UM\Working\Opto\Jackie671\placestim_day2\PRE\Jackie_PRE_2020-10-07_10-48-13\experiment1\recording1\continuous\Intan_Rec._Controller-100.0'
save_loc = np.nan